In prediction mode, the system has already learned with CEM and can
therefore use the incoming data to forecast a small step into the
future. This situation is depicted in
Figure 8.2. Here, the output motion of user B is
actually being generated by the learning system instead of directly
piping out of his vision system. It becomes quickly apparent that
nothing too interesting can happen as a result of this mode of
operation. The ARL system is simply operating as a filter (i.e. a
Kalman filter) since it is only generating some slightly modified
version,
of the original signal
.
When user B exits the scene, the system merely locks up
since the
is only being fed half of the signal (from user
A). The
vector only contains memory about user A and the
system has no memory of its own actions. Thus, only a portion of
is being updated and poor estimates using the pdf
will result. Thus, this mode of interaction is merely a
filtering where the output gestures of user B just seem smoothed.